Research On The City Car Travel Dynamic Route Choice Model That Considering The Triggering Event

In China, with the gradual application of Intelligent Transportation System (ITS), in particular the Advanced Traveler Information System (ATIS), travel information has become one of the important factors that affect the travel route travel decisions. The dynamic traffic information used in urban travel route planning can ease urban traffic congestion to some extent, and improve the efficiency of network. This paper aims to establish urban car travel Dynamic Path Selection Model that considering triggering event. To guide the city’s car travelers choose the right path to travel, and to avoid the impact of traffic accidents on the trip generated. Contents of this paper include:First, Set forth the concept and performance characteristics of trigger events. Analysis of the characteristics of trigger events in the dynamic traffic information; Based on the induction of traffic state short-term prediction method, select the k-Nearest Neighbor algorithm to predict the short-term traffic state; and use normal deviate algorithm to discriminate whether a triggering event occurs.After, proposed model assumptions and analysis the various factors that affect urban car travel route choice decisions. Combing the results triggering event discrimination, construction of the objective function; establish urban car travel Dynamic Path Selection Model that considering triggering event; Use Genetic algorithm to solve the model.Finally, in the study area within the actual trunk road network of Beijing, Using real-time traffic information and historical data, select the appropriate calculation parameters of k-Nearest Neighbor algorithm and normal deviate algorithm. Using urban car travel Dynamic Path Selection Model that considering triggering event to choose travel routes, analyze and evaluate the effect of the application of the model.